EP3318179A2 - Verfahren zur messung der atemfrequenz und der herzfrequenz mit einer doppelkamera eines smartphones - Google Patents

Verfahren zur messung der atemfrequenz und der herzfrequenz mit einer doppelkamera eines smartphones Download PDF

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Publication number
EP3318179A2
EP3318179A2 EP15897267.9A EP15897267A EP3318179A2 EP 3318179 A2 EP3318179 A2 EP 3318179A2 EP 15897267 A EP15897267 A EP 15897267A EP 3318179 A2 EP3318179 A2 EP 3318179A2
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EP
European Patent Office
Prior art keywords
signal
smartphone
heart rate
rgba
respiration rate
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Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
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EP15897267.9A
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English (en)
French (fr)
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EP3318179A4 (de
EP3318179B1 (de
Inventor
Yun-Young Nam
Young-Sun Kong
Bersain A. REYES
Ki H CHON
Natasa RELJIN
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Industry Academy Cooperation Foundation of Soonchunhyang University
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Industry Academy Cooperation Foundation of Soonchunhyang University
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Priority claimed from PCT/KR2015/013303 external-priority patent/WO2017003049A2/ko
Publication of EP3318179A2 publication Critical patent/EP3318179A2/de
Publication of EP3318179A4 publication Critical patent/EP3318179A4/de
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02416—Detecting, measuring or recording pulse rate or heart rate using photoplethysmograph signals, e.g. generated by infrared radiation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/024—Detecting, measuring or recording pulse rate or heart rate
    • A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves 
    • A61B5/053—Measuring electrical impedance or conductance of a portion of the body
    • A61B5/0535—Impedance plethysmography
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/08—Detecting, measuring or recording devices for evaluating the respiratory organs
    • A61B5/0816—Measuring devices for examining respiratory frequency
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/1126—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique
    • A61B5/1128—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb using a particular sensing technique using image analysis
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
    • A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
    • A61B5/113—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb occurring during breathing
    • A61B5/1135—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb occurring during breathing by monitoring thoracic expansion
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
    • A61B5/6813—Specially adapted to be attached to a specific body part
    • A61B5/6823—Trunk, e.g., chest, back, abdomen, hip
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
    • A61B5/6887—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient mounted on external non-worn devices, e.g. non-medical devices
    • A61B5/6898—Portable consumer electronic devices, e.g. music players, telephones, tablet computers
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7246—Details of waveform analysis using correlation, e.g. template matching or determination of similarity
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/74—Details of notification to user or communication with user or patient ; user input means
    • A61B5/742—Details of notification to user or communication with user or patient ; user input means using visual displays
    • A61B5/743—Displaying an image simultaneously with additional graphical information, e.g. symbols, charts, function plots
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
    • A61B5/7235—Details of waveform analysis
    • A61B5/7253—Details of waveform analysis characterised by using transforms
    • A61B5/7257—Details of waveform analysis characterised by using transforms using Fourier transforms

Definitions

  • the present invention relates to a method for simultaneously measuring a respiration rate and a heart rate using dual cameras of a smartphone.
  • smartphones contain various types of sensors, such as acceleration sensors, gyroscopes, touch sensors, temperature sensors, illumination sensors, gravity sensors, geomagnetic sensors, position sensors, etc., and high-performance cameras with innovative enhancements in hardware due to enhancements in computation speed.
  • the hardware performance enhancement of the smartphones does not simply mean function enhancement, but it enables various applications to be received from an application server and to be installed in smartphones, whereby application fields of the smartphones are dramatically expanded.
  • a smartphone is likely to be carried by a user at all times due to the characteristics of such a portable terminal.
  • smartphones are suitable for the medical field where the health condition of the user needs to be checked frequently.
  • various medical applications are installed in the smartphone such that the smartphone can monitor the health condition of the user in various ways.
  • the most common method of measuring respiration is to use respiratory sounds with chest movements or auscultation. These methods are constrained by accuracy or irregularity.
  • a sensor senses heart rate signals of a patient in an analog form and transmits the signals to a dedicated terminal through a USB cable, etc., and then the dedicated terminal converts the analog heart rate signal into digital heart rate signals using a micro control unit (MCU), an analog-to-digital converter (ADC), etc. to perform analysis.
  • MCU micro control unit
  • ADC analog-to-digital converter
  • a currently used electrocardiography device is problematic in that the MCU, etc. must be embedded in the dedicated terminal to convert the analog heart rate signals obtained through the heart rate sensor into the digital heart rate signals, and thus there are substantial errors in accuracy and manufacturing costs and sale prices are extremely high. Therefore, recently, in order to lower the manufacturing costs, an electrocardiography device with the MCU removed from the dedicated terminal has been developed.
  • the heart rate sensor must contain the MCU to perform analog-to-digital conversion, and thus the existing problems still cannot be solved.
  • An object of the present invention is to provide a method for simultaneously measuring a respiration rate and a heart rate using dual cameras of a smartphone.
  • the present invention is to enhance accuracy by simultaneously using respiration and PPG data.
  • an object of the present invention is to provide a method continuously monitoring a heart rate and a respiration rate so as to prevent death from cardiac arrest.
  • a method for measuring a respiration rate and a heart rate using dial cameras of a smartphone including: simultaneously collecting, at a first step, a PPG signal and visual data on chest and abdomen movements of a human; converting, at a second step, the visual data to an RGBA signal; applying, at a third step, a bandpass filter such that a frequency only within a range in the RGBA signal pass; removing, at a fourth step, first and last predetermined portions of the RGBA signal to which the band-pass filter is applied at the third step; selecting, at a fifth step, a color channel having a highest standard deviation from the RGBA signal where the predetermined portions are removed at the fourth step; applying, at a sixth step, a spline filter to the color channel selected at the fifth step; computing, at a seventh step, power spectrum density; and computing, at an eighth step, a heart rate and a respiration rate.
  • a respiration rate and a heart rate can be simultaneously measured with high accuracy using dual cameras of a smartphone.
  • a heart rate and a respiration rate can be continuously monitored such that sudden death and death from cardiac arrest can be prevented.
  • a smartphone 110 for a method for measuring a respiration rate and a heart rate using dual cameras of a smartphone according to an embodiment of the present invention, a smartphone 110, a chest impedance belt 130, an abdomen impedance belt 140, and a monitoring device 150 are provided.
  • a human wears impedance belts on the chest and abdomen to collect data.
  • the chest and abdomen impedance belts 130 and 140 are intended to measure an actual respiration rate of a human, and are coupled to the monitoring device 150.
  • a front side camera 160 of the smartphone 110 records chest and abdomen movements thereof and a rear side camera 120 of the smartphone 110 is in contact with the finger of the human for a preset time to measure a photoplethysmogram (PPG).
  • PPG photoplethysmogram
  • the measurement is performed with a turned on flash that is built in the rear side camera 120.
  • the human may verify a video recording the chest and abdomen movements through the front side camera 160 of the smartphone 110, a PPG signal being measured, and the respiration rate for the chest and abdomen movements in real time.
  • the respiration rate of the human measured using the front side camera 160 is compared with the respiration rate measured by the impedance belt.
  • Video signals of the video recorded by the front side camera 160 are stored in a range of 20 to 25 Hz, and audio signals are stored at 44.100 Hz and 16 bits. Also, mono audio signals have noise removed by applying a band-pass filter within a range of 500 to 5000 Hz.
  • FIG. 2 is a flowchart illustrating detailed steps of a method for simultaneously measuring a respiration rate and a heart rate using dual cameras of a smartphone according to an embodiment of the present invention.
  • step S210 visual data on chest and abdomen movements of the human is collected through the front side camera 160 of the smartphone and PPG signals are collected through the rear side camera 120.
  • the visual data and the PPG signal are simultaneously measured.
  • the visual data collected at the first step S210 is a video received from the front side camera 160 of the smartphone 110 with Android OS, and thus it is stored in the YUV420sp signal format. In order to process the visual data, it is necessary to convert the YUV420sp signal format into the RGBA signal format.
  • the OpenCV library is used to convert the signal format.
  • a band-pass filter is applied such that in the converted RGBA signal format, a frequency within a range passes.
  • a low-pass filter (f low ) of the band-pass filter is set to have a value of 0.08 Hz and a high-pass filter (f high ) is set to have a value of 2.1 Hz.
  • the low-pass filter is set to have a value of 0.667 Hz
  • the high-pass filter is set to have a value of 3.833 Hz.
  • the first and last portions of the RGBA signal to which the band-pass filter is applied are removed which about the first 10 seconds and the last 10 seconds of the signal. This is to remove noise existing in the video signal of the recorded video. Noise occurs at the beginning and the end of collecting the visual data due to actions related to correctly holding the smartphone, a calibration process, etc.
  • two different region of interest (ROI) images of 49 x 90 pixels are selected from a resolution of 320 x 240 pixels.
  • a resolution of 176 x 72 pixels is selected from a resolution of 176 x 144 pixels for all frames.
  • the brightness value (I) of each pixel may be obtained by an average value of a RGB channel in the ROI of one image, and Formula is as follows.
  • I x , y , t 1 D ⁇ I b x , y , t + ⁇ I g x , y , t + ⁇ I r x , y , t
  • D means the size of ROI.
  • a color channel with the highest standard deviation is selected from three color bands (red, green, and blue) while a green channel is selected to measure the heart rate.
  • the color channel with the highest standard deviation is selected in the RGBA signal with predetermined portions removed at the fourth step.
  • a spline filter is applied to the color channel selected at the fifth step.
  • the spline filter is a filter used for smoothing the amplitude of a signal.
  • an average intensity is used to extract an envelope of a filtered discrete signal, and then interpolation and smoothing are performed on the envelope signal.
  • the sixth step to which the spline filter for smoothing of the signal is applied includes: to obtain a smoothed amplitude envelope signal a(t) in the color channel selected at the fifth step, determining the maximum frequency of the a(t) at the sixth-1 step; obtaining an amplitude time series using cubic spline interpolation at the sixth-2 step; after interpolation, computing a class of an analytic signal of the a(t) at the sixth-3 step; and after determining the maximum value of the a(t), obtaining an average value using sliding window at the sixth-4 step.
  • Cubic spline interpolation at the sixth-2 step is a method used to connect two points that are separated from each other.
  • power spectrum density is computed using one of a Welch periodogram, autoregressive power spectrum analysis, and a regression correlation coefficient.
  • the power spectrum is computed using a 512-point fast Fourier transform (FFT) of autocorrelation using a window.
  • FFT fast Fourier transform
  • the correlation coefficient for analyzing similarity degree in a time domain between inspiration and expiration is shown in Formula 2.
  • corr x , y cov x , y ⁇ x , y
  • FIGS. 3a and 3b are graphs illustrating respiration rates for the chest and abdomen movements measured using the front side camera 160 of the smartphone 110.
  • correlation coefficient values are 0.3373 and 0.998, respectively.
  • a movement class is assigned to each signal using the correlation coefficient, and the class having a high correlation value is selected.
  • the correlation coefficient of the chest movement is higher than the correlation coefficient of the abdomen movement, the chest movement is selected.
  • FIG. 4a is a Bland-Altman graph illustrating the heart rate measured through the smartphone.
  • the Bland-Altman graph is a statistical method for comparing two measurement methods, and shows whether there is a difference between the average of two methods and the obtained value or whether there is a difference between an estimated value and an actual measured value.
  • the graph in FIG. 4a shows the differences in measured values between the continuous heart rate measured by the smartphone and corresponding ECG signals. Since there are five points of a scatter plot where z-scores based on standardized rates are outside the confidence interval of 95%, there is little difference between the two methods.
  • FIG. 4b is a correlation graph of two measurement methods.
  • the x-axis represents continuous heart rate measurement values using the smartphone, and the y-axis represents ECG measurement values.
  • the solid line indicates a regression line and the dotted line indicates Pearson correlation coefficients. Since points of a scatter plot are evenly scattered around the solid line rather spread, a correlation is high.
  • the heart rate and the respiration rate are computed using the result of the seventh step.
  • FIG. 5 is a view illustrating a graph of the respiration rate measured for the chest and abdomen movements and the PPG signal of the finger according to an embodiment of the present invention.
  • the respiration rate is measured using the chest and abdomen movements and the PPG signal is measured through the finger, and thus the human can easily observe the respiration rate and the PPG signal in real time.
  • the present invention is a very useful invention that can be widely applied to a health management system capable of managing heath.

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EP15897267.9A 2015-07-01 2015-12-07 Verfahren zur messung der atemfrequenz und der herzfrequenz mit einer doppelkamera eines smartphones Active EP3318179B1 (de)

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KR20150094242 2015-07-01
KR1020150171253A KR101777472B1 (ko) 2015-07-01 2015-12-03 스마트 폰의 듀얼 카메라를 이용한 호흡과 심장 박동 측정방법
PCT/KR2015/013303 WO2017003049A2 (ko) 2015-07-01 2015-12-07 스마트 폰의 듀얼 카메라를 이용한 호흡과 심장 박동 측정방법

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Cited By (2)

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IT202000014500A1 (it) * 2020-06-17 2021-12-17 Paco Adriano Di Metodo per fornire in tempo reale informazioni relative alle prestazioni cardiache e/o respiratorie di un individuo e relativo dispositivo
EP4085826A1 (de) 2021-05-04 2022-11-09 Koa Health B.V. Smartphone-herzfrequenz- und atemfrequenzbestimmung unter verwendung einer genauigkeitsmessungsgewichtung

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KR102487926B1 (ko) * 2018-03-07 2023-01-13 삼성전자주식회사 심장 박동을 측정하기 위한 전자 장치 및 방법
KR102560787B1 (ko) 2021-02-04 2023-07-26 삼성전자주식회사 생체정보 추정 장치 및 방법과, 이를 포함하는 전자장치

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US20150099987A1 (en) 2010-06-07 2015-04-09 Affectiva, Inc. Heart rate variability evaluation for mental state analysis
US9185353B2 (en) * 2012-02-21 2015-11-10 Xerox Corporation Removing environment factors from signals generated from video images captured for biomedical measurements
US9258300B2 (en) 2012-10-29 2016-02-09 Tzu Chi University ECG measuring device and method thereof
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KR101629901B1 (ko) * 2013-08-05 2016-06-13 상명대학교서울산학협력단 휴대용 단말기를 사용하는 맥파 신호 측정 방법
US20150124067A1 (en) * 2013-11-04 2015-05-07 Xerox Corporation Physiological measurement obtained from video images captured by a camera of a handheld device
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Publication number Priority date Publication date Assignee Title
IT202000014500A1 (it) * 2020-06-17 2021-12-17 Paco Adriano Di Metodo per fornire in tempo reale informazioni relative alle prestazioni cardiache e/o respiratorie di un individuo e relativo dispositivo
WO2021255616A1 (en) * 2020-06-17 2021-12-23 Di Paco Adriano Method for providing real-time information about the cardiac and/or respiratory performance of an individual, and corresponding device
EP4085826A1 (de) 2021-05-04 2022-11-09 Koa Health B.V. Smartphone-herzfrequenz- und atemfrequenzbestimmung unter verwendung einer genauigkeitsmessungsgewichtung

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KR20170004804A (ko) 2017-01-11
EP3318179A4 (de) 2019-03-20
EP3318179B1 (de) 2023-03-22
KR101777472B1 (ko) 2017-09-12

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